Effects of high‐pass filtering on MUAP metrics

Abstract

Previous observations suggest that elevated high-pass filter settings (1,600-3,200 HZ) can reveal greater motor unit action potential (MUAP) complexity (turns). We assessed the effect of high-pass filter settings (500, 1,000, 2,000 HZ) on MUAP metrics. MUAPs were recorded with a concentric needle and initially extracted by a decomposition software algorithm at 10 HZ-10 kHZ and further filtered offline at 500, 1,000, and 2,000 HZ. When reanalyzed by the decomposition software there were marked reductions in peak-peak amplitude, area, area-to-amplitude ratio, and duration at the 500 HZ filter with lesser subsequent reductions at higher filter settings. In contrast, turn and phase counts did not change significantly. Individual MUAPs tracked across filter settings showed rare increases in turn count at the 500 HZ setting but a subsequent decrease in counts with higher filter settings. We conclude that the routine use of elevated high-pass filters, as in quantitative EMG analysis, does not enhance turn count.

Sex differences in the modulation of the motor unit discharge rate leads to reduced force steadiness

“…The myoelectric signal gains were adjusted to maximize the resolution on the 16-bit analogue-to-digital converter (NI PCI-6052E; National Instruments, Austin, TX, USA), for offline analysis (Dell, Round Rock, TX, USA). The intramuscular myoelectric signal was band-pass filtered between 1000 and 10 000 Hz (Brownell and Bromberg 2009;Brown et al 2010) and sampled at 25 600 Hz using a computer-based data acquisition system (DASYLab; DASYTEC National Instruments, Amherst, NH, USA).…”

Comparing Different Filter-Parameter for Pre-Processing of Brain-Stimulation Evoked Motor Potentials

“…With the availability of digital calculators, a digital filter [ 9 ] was thereafter routinely used for processing the sEMG signals. Different types of digital filters and different parameter layouts have been used extensively in sEMG signal processing, but the use of filters in bio-signal analysis is not always as simple as it may look [ 4 , 10 ]. Distortions of electroencephalography (EEG) signals after filtering have been discussed recently [ 11 , 12 , 13 , 14 ], but there is no recommendation for filtering MEPs.…”